Immunosuppressive Condition and Medication Annotations for Admission Notes in the MIMIC-III Database

Immunosuppression due to underlying conditions or immunosuppressive medication
use increases the risk of morbidity and mortality in the context of infectious
disease. Identifying patients with immunosuppression is important for better
studying and understanding the impact of immunosuppression on critical care
outcomes. While structured data (e.g., diagnosis codes, medication orders)
from the electronic health record (EHR) can help identify patients with
immunosuppression, the reliability of structured data is limited as it can
miss more nuanced information that is only present in unstructured data, such
as patient notes.

We introduce a dataset for phenotyping immunosuppression, defined as
identification of a patient's immune status, based on admission notes. Patient
admission notes were extracted from the Medical Information Mart for Intensive
Care III (MIMIC-III) dataset, which contains health-related data and clinical
notes associated with patients who stayed in critical care units at Beth
Israel Deaconess Medical Center between 2001 and 2012. These notes were
manually annotated for the presence of several immunosuppressive conditions
and immunosuppressive medications.

Each admission note was independently annotated by two human annotators, and
discrepancies were reviewed by an attending critical care physician. Annotated
conditions include solid organ transplant, stem cell transplant, HIV, acute
leukemia, lymphoma, multiple myeloma, and immunoglobulin deficiency. Annotated
medications include azathioprine, cyclosporine, cyclophosphamide,
mycophenolate, rituximab, and tacrolimus. This dataset can be leveraged for
medical and computer science research, especially as related to the
application of natural language processing and large language models (LLMs) in
medicine. It can also be used as a starting point for research related to
immunosuppression in critically ill patients.